Currently, the diagnosis of a system under surveillance, which can be an electronics card, is done by an environmental measurement recording device. One such device is known under the English name “Time Stress Measurement Device, TMSD”. Such a device is described in the document FR-A1-2 844 902. This device comprises two sub-devices. The first portion is installed in the system to be monitored. And, the second portion is situated outside of the system to be monitored.
The first portion measures over time the environmental or factual parameters of the system to be monitored, such as the temperature, humidity, vibrations, shock, and so on. The first portion comprises a memory permitting the recording of measurements. After obtaining a complete profile of the recorded measurements, which can take several days, these recorded measurements are transferred in digital form to the second portion, which is a processing unit. The second portion analyzes the measurements recorded by the first portion in order to supply a system diagnosis. In effect, the processing unit extracts information from the group of these recorded measurements concerning the length of consumed life of the system to be monitored, of which the failure modes and their impacts are previously known. With this type of device, the use of recorded measurements is outside of the first group.
However, such a device for recording environmental parameters presents some disadvantages. In effect, with this type of device, it is necessary to initially obtain a complete profile of the measurements which are measured and recorded before the processing unit can determine the failures of the system to be monitored. This complete profile necessitates a pre-determined and necessary amount of data for analysis by the processing unit.
In one example, when the system to be monitored is an electronics card on board an airplane, the recorded data are not retrieved and analyzed by the processing unit until a complete profile is obtained. For example, a complete profile may be obtained after fifteen return trips by the airplane. Thus an important time lapse is observed before the recorded data are transferred to the processing unit. The results supplied by the processing unit are not immediate. In effect, the quantity of data to be analyzed is such that it takes several days before a percentage of length of consumed life of the system to be monitored is obtained. In consequence, this result concerning failures of the electronics card under surveillance is no longer appropriate when it is obtained. During the days which are required by the processing unit to produce a result, the electronics card may become faulty, without this fault being detected.
Currently, a faulty electronics card will not be detected or replaced before the complete profile analysis has been obtained. Therefore, the airplane with this type of device has the time to make, at least one trip with a defective part before the processing unit has provided the results enabling its detection. The non-replacement of a faulty part in time can have repercussions of important consequence in the domains of aeronautics, naval, automobile, and others.
Also, with this type of device, the data flow for obtaining the complete profile is very important. Because of this, the processing unit comprises very complex algorithms designed to process these exported data. One such processing unit comprises a standard data-simplification algorithm known under the English name “Ordered Overall Range, OOR”. This processing unit also comprises a standard cycle-counting algorithm, known under the English name “Rainflow”. With these algorithms, it is imperative to have the necessary group of data to obtain a complete profile, for functioning.
With this type of algorithm, the calculation resource requirements, as well as the memory resource requirements, are relatively large. Creation of such a device thus requires the implementation of complicated technologies due to demanding specifications. This complicated technology increases the global cost of the device.
Moreover, the existing algorithms of the processing unit of this known device cannot be used in an installed environment. Because they are so complicated, they cannot cope with the constraints of the limited resources of an installed environment, such as the low rate of calculation, the limited speed and the low memory capacity. These algorithms are also useless in an installed environment because of the need to wait for a complete profile before being able to apply them. They can therefore not be applied to each new measurement in order to make real time management possible.